Optimum design of the cored linear motor using experiment design

• Published in: Journal of mechanical science and technology Vol. 23; no. 8; pp. 2215 - 2223
• Main Authors: Seo, Sungill, Kim, Naksoo
• Format: Journal Article
• Language: English
• Published: Heidelberg Korean Society of Mechanical Engineers 01.08.2009; Springer Nature B.V; 대한기계학회
• Subjects: A.c. Machines; Analysis of variance; Applied sciences; Control; Cost function; Design engineering; Dynamical Systems; Electrical engineering. Electrical power engineering; Electrical machines; Engineering; Exact sciences and technology; Experimental design; Finite element method; Industrial and Production Engineering; Mathematical models; Mathematics; Mechanical Engineering; Motors; Office automation; Optimization; Probability and statistics; Ripples; Sciences and techniques of general use; Statistics; Studies; Vibration; 기계공학; Cored linear synchronous motor; Table of orthogonal array; Response surface methodology; Analysis of means; Analysis of variance; Thrust force; Performance evaluation; Statistical analysis; Computer integrated manufacturing; Precision engineering; Regression analysis; Variance analysis; Modeling; Optimization; Synchronous motor; Finite element method; Regression model; Experimental design; High speed; Cost function; Ripple; Response surface; Linear motor; Thrust
• ISSN: 1738-494X; 1976-3824
• DOI: 10.1007/s12206-009-0514-1

Recently, a linear motor has been becoming widely popular in office automation (OA) and factory automation (FA) systems due to its simple structure, high-speed operation, and precise positioning. In this study, a cored linear motor was designed to have a large thrust and small ripple because these are considered as indicators of motor performance. The thrust and ripple of the linear motor can be calculated by a finite element method (FEM) commercial program such as ANSYS. To design the cored linear motor, first, the design variables were selected through ANOM and ANOVA. The response surface method was applied to formulate the cost function of the second-order regression model, which can evaluate motor performance. By optimizing the cost function, it was possible to realize quickly the optimum design for a cored linear motor. As a result, the performance of the motor was improved.